Reverse engineering of the spindle assembly checkpoint

Genetic interactions derived from high-throughput phenotyping of 6589 yeast cell cycle mutants

Over the last 30 years, computational biologists have developed increasingly realistic mathematical models of the regulatory networks controlling the division of eukaryotic cells. These models capture data resulting from two complementary experimental approaches: low-throughput experiments aimed at extensively characterizing the functions of small numbers of genes, and large-scale genetic interaction screens that provide a systems-level perspective on the cell division process. The former is insufficient to capture the interconnectivity of the genetic control network, while the latter is fraught with irreproducibility issues. Here, we describe a hybrid approach in which the 630 genetic interactions between 36 cell-cycle genes are quantitatively estimated by high-throughput phenotyping with an unprecedented number of biological replicates. Using this approach, we identify a subset of high-confidence genetic interactions, which we use to refine a previously published mathematical model of the cell cycle. We also present a quantitative dataset of the growth rate of these mutants under six different media conditions in order to inform future cell cycle models.

Fluorescent foci quantitation for high-throughput analysis

A number of cellular proteins localize to discrete foci within cells, for example DNA repair proteins, microtubule organizing centers, P bodies or kinetochores. It is often possible to measure the fluorescence emission from tagged proteins within these foci as a surrogate for the concentration of that specific protein. We wished to develop tools that would allow quantitation of fluorescence foci intensities in high-throughput studies. As proof of principle we have examined the kinetochore, a large multi-subunit complex that is critical for the accurate segregation of chromosomes during cell division. Kinetochore perturbations lead to aneuploidy, which is a hallmark of cancer cells. Hence, understanding kinetochore homeostasis and regulation are important for a global understanding of cell division and genome integrity. The 16 budding yeast kinetochores colocalize within the nucleus to form a single focus. Here we have created a set of freely-available tools to allow high-throughput quantitation of kinetochore foci fluorescence. We use this 'FociQuant' tool to compare methods of kinetochore quantitation and we show proof of principle that FociQuant can be used to identify changes in kinetochore protein levels in a mutant that affects kinetochore function. This analysis can be applied to any protein that forms discrete foci in cells.

Modeling the mitotic regulatory network identifies highly efficient anti-cancer drug combinations

Targeting mitotic regulation is recognized as an important strategy for cancer therapy. Aurora A/B kinase and polo-like kinase 1 (PLK1) are the key mitotic regulators, and many inhibitors have been developed. Combinations of these inhibitors are anticipated to be more effective therapeutics compared with single-inhibitor treatments; however, a systematic analysis of the combined effects is lacking. Here, we constructed the first mammalian cell mitotic regulation network model, which spans from mitotic entry to anaphase initiation, and contains all key mitotic kinase targets. The combined effects of different kinase inhibitors and microtubule inhibitors were systematically explored. Simultaneous inhibition of Aurora B and PLK1 strongly induces polyploidy. Microtubule inhibitor dosage can be significantly reduced when combined with a PLK1 inhibitor. The efficacy of these inhibitor combinations was validated by our experimental results. The mitotic regulatory network model provides a platform to study the complex interactions during mitosis, enables identification of mitotic regulators, and determines targets for drug discovery research. The suggested use of combining microtubule inhibitors with PLK1 inhibitors is anticipated to enhance microtubule-inhibitor tolerance in a wide range of patients.

Towards a quantitative understanding of mitotic spindle assembly and mechanics

The 'simple' view of the mitotic spindle is that it self-assembles as a result of microtubules (MTs) randomly searching for chromosomes, after which the spindle length is maintained by a balance of outward tension exerted by molecular motors on the MTs connecting centrosomes and chromosomes, and compression generated by other motors on the MTs connecting the spindle poles. This picture is being challenged now by mounting evidence indicating that spindle assembly and maintenance rely on much more complex interconnected networks of microtubules, molecular motors, chromosomes and regulatory proteins. From an engineering point of view, three design principles of this molecular machine are especially important: the spindle assembles quickly, it assembles accurately, and it is mechanically robust--yet malleable. How is this design achieved with randomly interacting and impermanent molecular parts? Here, we review recent interdisciplinary studies that have started to shed light on this question. We discuss cooperative mechanisms of spindle self-assembly, error correction and maintenance of its mechanical properties, speculate on analogy between spindle and lamellipodial dynamics, and highlight the role of quantitative approaches in understanding the mitotic spindle design.